Journal of Risk and Uncertainty

, Volume 49, Issue 2, pp 125–140 | Cite as

The neural correlates of contractual risk and penalty framing

  • W. Gavin Ekins
  • Andrew M. Brooks
  • Gregory S. Berns


Standard economic theory treats contractual risk the same as risk experienced in a lottery, but the transfer of risk from principal to agent may change the perception of risk. Previous experimental studies have shown that positive and negative framing affects both gambles and incentive contracts. An agent’s perception of bonus and penalty framing in a contract can determine the extent to which lottery risk and contractual risk are similar. We designed an experiment that tested the effect of bonus and penalty framed contracts on behavior under an implicit chance of failure. Moreover, we used functional magnetic resonance imaging (fMRI) to observe brain activity while participants viewed the contracts and purchased precautionary measures. We found that the dorsal striatum was more active during a penalty frame than a bonus frame. The study suggests that risk experienced by agents in an incentive contract is not comparable to risk experienced as a lottery.


Risk Incentive contracts Framing effects fMRI Striatum 

JEL Classifications

C91 D81 D86 D87 


  1. Abler, B., Walter, H., Erk, S., Kammerer, H., & Spitzer, M. (2006). Prediction error as a linear function of reward probability is coded in human nucleus accumbens. NeuroImage, 31(2), 790–795.CrossRefGoogle Scholar
  2. Allen, D. W., & Lueck, D. (1995). Risk preferences and the economics of contracts. The American Economic Review, 85(2), 447–451.Google Scholar
  3. Balleine, B. W., Delgado, M. R., & Hikosaka, O. (2007). The role of the dorsal striatum in reward and decision-making. The Journal of Neuroscience, 27(31), 8161–8165.CrossRefGoogle Scholar
  4. Berns, G. S., & Bell, E. (2012). Striatal topography of probability and magnitude information for decisions under uncertainty. NeuroImage, 59(4), 3166–3172.CrossRefGoogle Scholar
  5. Boynton, G. M., Engel, S. A., Glover, G. H., & Heeger, D. J. (1996). Linear systems analysis of functional magnetic resonance imaging in human V1. The Journal of Neuroscience, 16(13), 4207–4221.Google Scholar
  6. Brink, A. (2008). The effects of risk preference and loss aversion on individual behavior under bonus, penalty, and combined contract frames. Electronic Theses, Treatises and Dissertations.Google Scholar
  7. Delgado, M. R. (2007). Reward-related responses in the human striatum. Annals of the New York Academy of Sciences, 1104(1), 70–88.CrossRefGoogle Scholar
  8. Delgado, M., Locke, H., Stenger, V., & Fiez, J. (2003). Dorsal striatum responses to reward and punishment: Effects of valence and magnitude manipulations. Cognitive, Affective, & Behavioral Neuroscience, 3(1), 27–38.CrossRefGoogle Scholar
  9. Frederickson, J. R., & Waller, W. (2005). Carrot or stick? Contract frame and use of decision-influencing information in a principal-agent setting. Journal of Accounting Research, 43(5), 709–733.CrossRefGoogle Scholar
  10. Gervais, S., Heaton, J. B., & Odean, T. (2011). Overconfidence, compensation contracts, and capital budgeting. The Journal of Finance, 66(5), 1735–1777.CrossRefGoogle Scholar
  11. Goetz, C. J., & Scott, R. E. (1977). Liquidated damages, penalties and the just compensation principle: Some notes on an enforcement model and a theory of efficient breach. C Law Rev, 77, 554.Google Scholar
  12. Hannan, R., Hoffman, V., & Moser, D. (2005). Bonus versus penalty: Does contract frame affect employee effort? In A. Rapoport & R. Zwick (Eds.), Experimental business research (Vol. II, pp. 151–169). New York: Springer.CrossRefGoogle Scholar
  13. Knutson, B., Fong, G., Adams, C., Varner, J., & Hommer, D. (2001). Dissociation of reward anticipation and outcome with event-related fMRI. Neuroreport, 12(17), 3683–3687.CrossRefGoogle Scholar
  14. Lazear, E. (1991). Labor economics and the psychology of organizations. Journal of Economic Perspectives, 5(2), 89–110.CrossRefGoogle Scholar
  15. Lewis, T. R. (1980). Bonus and penalties in incentive contracting. Bell Journal of Economics, 11(1), 292–301.CrossRefGoogle Scholar
  16. Luft, J. (1994). Bonus and penalty incentives contract choice by employees. Journal of Accounting and Economics, 18(2), 181–206.CrossRefGoogle Scholar
  17. Martino, B. D., Camerer, C. F., & Adolphs, R. (2010). Amygdala damage eliminates monetary loss aversion. Proceedings of the National Academy of Sciences, 107(8), 3788–3792.CrossRefGoogle Scholar
  18. O’Doherty, J., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004). Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science, 304(5669), 452–454.CrossRefGoogle Scholar
  19. Penny, W., Flandin, G., & Trujillo-Barreto, N. (2007). Bayesian comparison of spatially regularised general linear models. Human Brain Mapping, 28(4), 275–293.CrossRefGoogle Scholar
  20. Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315(5811), 515–518.CrossRefGoogle Scholar
  21. Yacubian, J., Gläscher, J., Schroeder, K., Sommer, T., Braus, D. F., & Büchel, C. (2006). Dissociable systems for gain- and loss-related value predictions and errors of prediction in the human brain. The Journal of Neuroscience, 26(37), 9530–9537.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • W. Gavin Ekins
    • 1
  • Andrew M. Brooks
    • 2
  • Gregory S. Berns
    • 3
  1. 1.Department of Economics and Center for NeuropolicyEmory UniversityAtlantaUSA
  2. 2.Center for NeurpolicyEmory UniversityAtlantaUSA
  3. 3.Department of Economics and Center for NeuropolicyEmory UniversityAtlantaUSA

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